摘要: |
Roadway design guidebooks are defined by precise measurements regarding lane widths, shoulder widths, superelevation, curb heights, paint markings, etc. The so-called aesthetic qualities of a streetscape –tree canopy, building frontage, seating, etc. – receive less attention and measuring them has been an arduous and subjective endeavor. The existing literature is beginning to show that that such factors can play a role in active transportation, road safety, health, and economic outcomes. Yet, researchers remain conflicted on these associations. This lack of consensus is partially due to the inability to objectively measure these street elements on a large-scale basis.
This research will examine the use of LiDAR (Light Detection and Ranging) technology to measure urban streetscapes. LiDAR is a highly precise remote sensing technology that uses light pulses to measure distances to objects. Using 3D volumetric pixels, known as voxels, the research team will test two quality levels of LiDAR to objectively measure how well various streetscape features can be assessed and measured. The intent is to devise new methods for objectively measuring streetscapes and features within streetscapes and to understand what streetscape features can be derived and analyzed with each LiDAR quality level. The team also seeks to use these methods to develop a LiDAR-based measure that represents street enclosure – and the degree to which a street feels smaller via a combination of horizontal and vertical definition – which is hypothesized to be a significant factor associated with how people perceive and behave within the built environment, including with respect to vehicle speeds and road safety outcomes. |